flypig.co.uk

List items

Items from the current list are shown below.

Blog

11 Apr 2020 : Google/Apple's “privacy-safe contact tracing“, a summary #
As I discussed yesterday, Google and Apple recently announced a joint privacy-preserving contact tracing API aimed at helping people find out whether they'd been in contact with someone who subsequently tested positive for COVID-19.

We've already relinquished so many rights in the fight against COVID-19, it's important that privacy isn't another one, not least because the benefit of contact tracing increases with the number of people who use it, and if it violates privacy it'll rightly put people off.

So I'm generally positive about the specification. It seems to be a fair attempt to provide privacy and functionality. Not only that, it's providing a benchmark for privacy that it would be easy for governments to fall short of if the spec weren't already available. Essentially, any government who now provides less privacy than this, is either incompetent, or has alterior motives.

But what does the spec actually say? Apple and Google have provided a decent high-level summary in the form of a slide deck, from which the image below is taken. They've also published a (non-final) technical specification. However, for me the summary is too high-level (it explains what the system does, but not how it works) and the technical specs are too low-level (there's too much detail to get a quick understanding). So this is my attempt at a middle-ground.
 
A high-level overview of the approach

There are three parts to the system. There's the OS part, which is what the specification covers; there's an app provided by your regional health authority; and there's a server run by your regional health authority (or more likely, a company the health authority subcontracted to). They all act together to provide the contact tracing service.
 
  1. Each day the user's device generates a random secret $k$, which stays on the user's device for the time being.
  2. The device then broadcasts BLE beacons containing $h = H(k, c)$ where $H$ is a one-way hash function and $c$ is a counter. Since $k$ can't be derived from $h$, and since no pair of beacons $h_1, h_2$ can be associated with one another, the beacons can't in theory be used for tracking. This assumes that the BLE subsystem provides a level of tracking-protection, for example through MAC randomisation. Such protections don't always work, but at least in theory the contact-tracing feature doesn't make it any worse.
  3. The device also listens for any beacons sent out by other users and stores any it captures locally in a list $b_1, b_2, \ldots$.
  4. If a user tests positive for COVID-19 they are asked to notify the regional health authority through the app. This involves the app uploading their secret $k$ for the day to a central database run by the regional health authority (or their subcontractor). From what I can tell, neither Apple nor Google need to be involved in the running of this part of the system, or to have direct access to the database. Note that only $k$ is uploaded. Neither the individual beacons $h_1, h_2, \ldots$ sent, nor the beacons $b_1, b_2, \ldots$ received, need to be uploaded. This keeps data quantities down.
  5. Each day the user's phone also downloads a list $k_1, k_2, \ldots, k_m$ of secrets associated with people who tested positive. This is the list collated each day in the central database. These keys were randomly generated on the user's phone and so are pseudonymous.
  6. The user's phone then goes through the list and checks whether one of the $k_i$ is associated with someone they interacted with. It does this by re-calculating the beacons that were derived from this secret: $H(k_i, 1), H(k_i, 2), \ldots, H(k_i, m)$, and compares each against every beacon it collected the same day.
  7. If there's a match $H(k_i, j) = b_l$, then the user is alerted that they likely interacted with someone who has subsequently tested positive. Because the phone also now knows the counter $j$ used to generate the match, it can also provided a time for when the interaction occurred.

This is a significant simplification of the protocol, but hopefully gives an idea of how it works. This is also my interpretation based on reading the specs, so liable to error. By all means criticise my summary, but please don't use this summary to criticise the original specification. If you want to do that, you should read the full specs.

Because of the way the specification is split between the OS and the app, the BLE beacons can be transmitted and received without the user having to install any app. It's only when the user tests positive and wants to notify their regional health authority, or when a user wants to be notified that they may have interacted with someone who tested positive, that they need to install the app. This is a nice feature as it means there's still a benefit even if users don't immediately install the app.

One of the big areas for privacy concern will be the behaviour of the apps provided by the regional health authorities. These have the ability to undermine the anonymity of the system, for example by uploading personal details alongside $k$, or by tracking the IP addresses as the upload takes place. I think these are valid concerns, especially given that governments are notorious data-hoarders, and that the system itself is unlikely to be built or run by a health authority. It would be a tragic missed opportunity if apps do undermine the privacy of the system in this way, but unfortunately it may also be difficult to know unless the sourcecode of the apps themselves is made available.
 

Comments

Uncover Disqus comments